To behave adaptively, individuals must learn associations between reward outcomes and features of the environment, and use these associations to inform behavior in novel situations. Previous research in animal models has demonstrated that the neural systems engaged during associative learning can influence such generalization behaviors, such that adaptive generalization requires engagement of the hippocampus. However, the majority of research in human subjects has investigated striatal-guided reward learning and generalization, often during multi-trial, probabilistic feedback learning. In everyday life, reward values are often acquired after only a single experience or episode; the neural mechanisms guiding such single-trial reward feedback learning are undefined. The current proposal advances the claim that single-trial reward feedback learning and generalization may be characterized by the interactions between reinforcement learning and episodic memory systems. We will test this claim by combining behavioral methods, computational modeling, and high-resolution neuroimaging. We will characterize the neural systems engaged during the acquisition of single-trial reward feedback associations using hi-resolution fMRI (Aim 1). Further, we will characterize how associative learning via single-trial reward feedback contributes to generalization behavior using reinforcement-learning modeling (Aim 2) and model-based fMRI (Aim 3). We predict that (1) single-trial reward-feedback learning will engage interactions between the striatum and hippocampus during associative learning, and (2) the interaction between these systems will promote adaptive generalization of reward associations. The knowledge obtained from this proposal will advance our understanding of the neurobiology of reward learning and provide evidence for the mechanisms underlying healthy and impaired reward-related behaviors such as drug addiction.